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Optimization of the performance of a voltage measuring station using genetic algorithm.

Mehbub A K Nooruddin¹, Subhasish Roy¹, Nilotpal Bhandary¹

¹Department of Physics, Visva-Bharati, Santiniketan PIN 731235, India.

The Review of Scientific Instruments

|July 10, 2021

Summary

This study introduces a genetic algorithm (GA) for optimizing voltage measuring stations. The GA-based system self-calibrates by learning from past measurements to improve accuracy.

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Area of Science:

Electrical Engineering
Metrology
Computational Intelligence

Background:

Accurate voltage measurements are critical for various scientific and industrial applications.
Regular calibration is essential for maintaining instrument performance but can be time-consuming and costly.

Purpose of the Study:

To develop and evaluate a genetic algorithm (GA)-based system for optimizing voltage measuring station performance.
To enable automated, self-calibration of instruments requiring frequent accuracy checks.

Main Methods:

Implementation of a genetic algorithm (GA) for performance optimization.
Development of a GA-based correction module to store and utilize historical measurement data (value-time pairs).
Integration of sanity-checking routines against known voltage standards for auto-calibration.

Main Results:

The GA-based correction module effectively uses past data to refine current voltage readings.
The system demonstrates self-calibration capabilities through periodic checks against zero and standard voltages.
Developed dedicated GA libraries and a correction module for this application.

Conclusions:

The proposed GA-based approach offers an effective method for optimizing voltage measuring station performance.
The system provides a robust solution for instruments needing regular calibration, enhancing accuracy and reliability.
The developed system serves as a valuable testbed for researching and advancing self-calibration algorithms.